In ensemble learning, does accuracy increase depending on the number of models you want to combine?
Yes, you can. Let's say you have 5 classes named a,b,c,d,e. You fit your data into a SVM Classifier and a Random Forest Classifier. Assume that, SVM classified &quot;a&quot; and &quot;b&quot; class well and RFC classified &quot;c&quot;,&quot;d&quot;,&quot;e&quot; well. So, ensembling these two models is going to increase accuracy  dramatically. Ensemble learning is really good when a model generating many &quot;False-Positive&quot; and &quot;False-Negative&quot;. You can also use weighted ensemble learning methods. You can set greater weights for reliable models &amp; lower weights for untrustable models.